IoT based Machine Learning Techniques for Climate Predictive Analysis
M.K. Nallakaruppan1, U. Senthil Kumaran2
1M.K. Nallakaruppan, Assistant Professor, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
2U. Senthil Kumaran, Associate Professor, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
Manuscript received on 06 February 2019 | Revised Manuscript received on 19 February 2019 | Manuscript Published on 04 March 2019 | PP: 171-175 | Volume-7 Issue-5S2 January 2019 | Retrieval Number: ES2026017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The continuous research in the fields of Internet of Things and Machine Learning has offered ascend to various weather forecast models. However, the issue of precisely foreseeing or anticipating the weather still perseveres. This paper is an application of Internet of Things and Machine Learning algorithms like Decision Tree and Time Series Analysis. The Internet of Things actually signifies ‘things’ (e.g. sensors and other shrewd gadgets) which are associated with the web. Despite the fact that this may appear to be irrelevant, ‘things’ represent a new and progressively, critical foundation requiring their own particular devoted technological system. The obtained results from the Machine Learning demonstrated that the time series method forecasts the weather more accurately for a larger duration of time.
Keywords: Weather Prediction, Machine Learning, Internet of Things, Decision Tree, Support Vector Machines, Time Series.
Scope of the Article: Machine Learning